This Project Grant award of $185,428 from the National Science Foundation (NSF) Office of Advanced Cyberinfrastructure, under the NSF's Computer and Information Science and Engineering (CISE) program (CFDA 47.070), will fund research at Auburn University to develop an edge-friendly cyberinfrastructure that enables efficient, secure, and privacy-preserving federated learning (FL) for intelligent transportation system (ITS) applications.
The project aims to advance FL capabilities on resource-limited edge devices, such as smart traffic cameras and dashcams, to enable collaborative training of shared machine learning models across distributed ITS data while keeping the data local. The research will address key challenges around efficiency, security, and privacy for broad adoption and real-world deployment of FL in ITS. Outcomes will include open-source software tools, a distributed testbed using NVIDIA Jetson Nano devices, and educational activities to benefit the ITS research community. The 3-year project period runs from September 1, 2023 to August 31, 2026.
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